Intuitive neuromyoelectric control of a dexterous bionic arm using a modified Kalman filter

Abstract

Background: Multi-articulate prostheses are capable of performing dexterous hand movements. However, clinically available control strategies fail to provide users with intuitive, independent and proportional control over multiple degrees of freedom (DOFs) in real-time. New Method: We detail the use of a modified Kalman filter (MKF) to provide intuitive, independent and proportional control over six-DOF prostheses such as the DEKA "LUKE" Arm. Input features include neural firing rates recorded from Utah Slanted Electrode Arrays and mean absolute value of intramuscular electromyographic (EMG) recordings. Ad-hoc modifications include thresholds and nonunity gains on the output of a Kalman filter. Results: We demonstrate that both neural and EMG data can be combined effectively. We also highlight that modifications can be optimized to significantly improve performance relative to an unmodified Kalman filter. Thresholds significantly reduced unintended movement and promoted more independent control of the different DOFs. Gain were significantly greater than one and served to amplify participant effort. Optimal modifications can be determined quickly offline and translate to functional improvements online. Using a portable take-home system, participants performed various activities of daily living. Comparison with Existing Methods: In contrast to pattern recognition, the MKF allows users to continuously modulate their force output, which is critical for fine dexterity. The MKF is also computationally efficient and can be trained in less than five minutes. Conclusions: The MKF can be used to explore the functional and psychological benefits associated with long-term, at-home control of dexterous prosthetic hands. HIGHLIGHTS:• Neural and electromyographic signals can be used together to estimate motor intent • Ad-hoc thresholds and gains improve prosthetic control by reducing unintended movement • Thresholds and gains can be optimized offline and translate to functional improvements online

Long-Term Performance of Utah Slanted Electrode Arrays and Intramuscular Electromyographic Leads Implanted Chronically in Human Arm Nerves and Muscles

“…The first amputee (subject 5; S5) was a 43-year-old male whose left and right forearms were amputated 24 years prior due to trauma [9,18]. The second amputee (subject 6; S6) was a 57-year-old male whose left foot and left forearm were amputated 13 years prior due to trauma [5,6,10,12]. The third amputee (subject 7; S7) was a 48-year-old male whose right forearm was electively amputated due to chronic Complex Regional Pain Syndrome with simultaneous intraoperative implantation of the USEA and iEMG devices [4,5].…”

“…We implanted two USEAs each in S5 and S6 (one in the median nerve and one in the ulnar nerve), and three USEAs in S7 (two in the median nerve and one in the ulnar nerve), as described in [5] (Fig. 1).…”

“…USEAs and iEMGs were surgically removed after 425 and 503 days for participants S6 and S7, respectively, as the result of prior mutual agreements between the volunteer participants and the experimenters regarding study duration. Additional information regarding the surgical procedure can be found in [5].…”

“…A total of 13, 65, and 46 datasets were collected for participants S5, S6, and S7, respectively. Additional experimental sessions were performed with the participants and have been reported previously [4][5][6]9,10,12].…”

“…The Utah Slanted Electrode Array (USEA) consists of a 10 × 10 grid of electrodes with depths from 0.5 to 1.5 mm that penetrate peripheral nerves to enable single-unit neural recordings and intraneural microstimulation [1]. USEAs implanted in the peripheral nerves serve as a bi-directional sensorimotor neural interface, and have now been used to reanimate motionless limbs [2,3], to provide intuitive control of and sensory feedback from bionic arms [4][5][6][7][8][9], and to alleviate neuropathic pain [10,11]. The high electrode count and intrafasicular nature of the USEA yields improved specificity [6,12].…”